Data warehouses are typically used for analyzing business activities and perform decision making based on the analyzed activities. The information within a data warehouse can be collected from a many different databases. Data warehouses use measures and dimensions, respectively, to summarize and categorize data. Data warehouses also comprise various data schemas that describe tables, fields within the tables, and the relationships between tables and fields.
During the life-cycle of a relational database table within the data warehouse, it is common to perform schema changes such as adding, removing or renaming columns in tables, creating, dropping or renaming tables, and more as the business needs change. Currently, all these changes are destructive, that is, they override the previous schema of the database. Thus, it is not possible to examine historical data according to the structure it had at the time it was created.
Therefore a need exists to overcome the problems with the prior art as discussed above.